Biomedical subjects

Jonathan F Bard

Publications and source records attributed to Jonathan F Bard.

2 recordsLinked to original sources

PubMed2006

Incremental changes in the workforce to accommodate changes in demand.

In many service organizations, rosters must be constructed weekly or monthly as demand and available personnel change. Once the permanent workforce is fixed, it may not be possible to alter its composition easily, implying that expensive contract labor may be the only option to cover shortages. With respect to nursing resources, this means calling in part-timers, casuals, or agency nurses on a daily basis, or hiring travelers for up to several months at a time. This paper addresses the latter option and presents two models that can be used to solve what we call the nurse addition problem. The first was originally developed to solve the midterm preference scheduling problem and is based on a pattern-view formulation. The second is derived from a shift-view formulation and is solved with a branch-and-price algorithm. In either case, the objective is to hire up to some predetermined number of nurses and assign them midterm schedules that minimize the maximum amount of uncovered shifts per day in the planning horizon. Each roster selected for a new nurse must satisfy a set of hard constraints related to the total working hours, workstretches, time between shifts, and weekend requirements, and a set of soft constraints related

Humans↗

PubMed2005

Short-term nurse scheduling in response to daily fluctuations in supply and demand.

Hourly changes in patient census and acuity require hospitals to update their staffling needs on a continuing basis. This paper discusses the problem that management faces several times a day as the demand for nursing services departs from the planned schedule. Prior to the start of each shift, the number of nurses who are scheduled to be on duty over the next 24 hours is compared with the number actually available, and if shortages exist a series of decisions have to be made to ensure that each unit in the hospital has sufficient coverage. These decisions involve the use of overtime, outside nurses, and floaters. To address this problem, we have developed an integer programming model that takes the current set of rosters for regular and pool nurses and the expected demand for the upcoming 24 hours as input, and produces a revised schedule that makes the most efficient use of the available resources. The model is formulated and solved at a hospital-wide level rather than for each unit separately. To determine its applicability, a representative set of scenarios was investigated using data obtained from a medium-size facility in the U.S. with 14 units. The results indicate that problem instances with up to 120 nurses can be solved in a negligible amount of time.

Humans↗